DATA WAREHOUSE OPTIMIZATION WITH HADOOP

Data warehouses have been the foundation for business analytics for many years, and have grown to support increasing data volumes as well as analytics and ETL workflows. Yet over time, some data becomes older and is used infrequently or not at all. And ETL workflows implemented as transformations inside the data warehouse can grow to occupy significant CPU cycles, impacting resources that support critical analytics processes.

Hadoop provides a modern complement to the enterprise data warehouse with significantly lower cost for storing and processing large volumes of data. With Hadoop, enterprises can offload less valuable data from their data warehouse as well as some workflows like ETL, freeing up valuable resources in the data warehouse while reducing total cost of ownership.

To capitalize on this opportunity, enterprises need to accurately identify the right data and workflows that can be offloaded, and understand the potential impact of moving them on their existing users, reports, and IT resources. This can be challenging given the complex and multi-layered enterprise data warehouse environment.

Attunity Visibility can help with a unique data usage and analytics platform that supports all leading data warehouse platforms, including Teradata, Exadata and IBM Pure Data for Analytics (Netezza). In addition, Attunity provides software to execute the actual data transfer and redirect data ingest directly to Hadoop.

Augment and Optimize Your Data Warehouse

Attunity Visibility provides comprehensive data usage and workload analytics for all the leading data warehouse platforms. With information and insight based on in-depth and multi-dimensional analysis of the data warehouse environment, it can be easily used in dashboards and reports to enable informed, fact-based planning for offload and migration to Hadoop.

With Attunity Visibility, enterprises can:

Offload data intelligently, by identifying unused and infrequently used DW data to offload to Hadoop, freeing up valuable DW capacity and resources.

Offload ETL workflows, by discovering ETL-intensive workflows that also can be moved to Hadoop, including in-depth analysis down of their SQL statements.

Free EDW Resources, by offloading data and workflows, making more resources available to support valuable business analytic needs

Offload Data Efficiently to Hadoop

With Attunity Replicate, enterprises can:

Accelerate data offload, by replicating data from their data warehouse to Hadoop.

Ingest data to Hadoop from many data sources, enabling IT to feed data to Hadoop to support offloaded ETL processes

Load Hadoop data to the EDW, by replicating results from ETL processes done in Hadoop and loading them efficiently to any EDW